Vegetation indices as a Tool for Mapping Sugarcane Management Zones

Abstract In precision agriculture, the adoption of management zones (MZs) is one most effective strategies for increasing agricultural efficiency. Currently, MZs in sugarcane production areas are classified based on conventional soil sampling, which demands a lot time, labor and financial resources. Remote sensing (RS) combined with vegetation indices (VIs) promising alternative to support traditional classification method, especially because it does not require physical access interest, cost-effective less labor-intensive, allows fast easy coverage large areas. The objective this study was evaluate ability normalized difference index (NDVI) two-band enhanced (EVI2) classify MZs, compared Brazilian Cerrado biome (savannah), where about half Brazil´s takes place. This used historical crop data from 5,500 fields three years (2015 2018) NDVI EVI2 values 14 images acquired by Landsat 8 satellite 2015 2018 Google Earth Engine (GEE). Although improvements still necessary encouraged, new methodology classifying according VIs proposed study. correlated using whereas more sensitive biomass variations between and, therefore, could better discriminate MZs. measured crops aged 180 240 days rainy season proved be best strategy RS, MZ A, example, had 0.37, E, an 0.32.